Veunex is hiring for an fresher entry level Artificial Intelligence Engineer role in India

Position:

• Artificial Intelligence Engineer

Company:

• Veunex

Location:

• Bengaluru, Karnataka, India

Job type:

• Full-time

Job mode:

• Onsite

Job requisition id:

• Not specified

Years of experience:

• 0–3 years

Company Description:

• Veunex is a technology-driven company redefining safety automation in high-risk industrial sectors, particularly Oil & Gas.

• The company has created the world’s first AI-powered safety automation platform, focusing on real-time risk detection and actionable insights.

• Veunex functions as a Virtual HSE Assistant that assists professionals in streamlining health, safety, and environmental responsibilities through intelligent automation.

• It facilitates rapid and reliable communication around risk assessments, observations, and other safety parameters.

• With a team of 11 to 50 employees, Veunex emphasizes innovation, agility, and tangible impact on safety outcomes.

• By integrating cutting-edge artificial intelligence with human-centric safety protocols, the company is helping transform how organizations approach safety and compliance.

• The platform’s adaptability enables it to scale from small sites to large offshore rigs while maintaining performance.

• As a growing startup, Veunex offers an energetic and close-knit work environment where every contribution influences the bigger picture.

• The company is committed to saving lives and improving operations across the energy sector through smart automation.

• Veunex is gaining recognition as a pioneer in operationalizing AI in physically intensive and remote environments.

Profile Overview:

• This entry-level Artificial Intelligence Engineer role is crafted for hands-on professionals eager to deploy AI in live field operations.

• The role combines technical expertise in AI and data engineering with a deep understanding of practical safety challenges in Oil & Gas.

• The engineer will work across the spectrum of model development, data optimization, and client deployment, helping bridge technology and execution.

• The engineer will be instrumental in training, optimizing, and deploying models tailored for safety-critical use cases.

• A significant portion of the work involves fieldwork, including visiting and deploying solutions at offshore and onshore locations.

• The role demands comfort with uncertainty, shifting priorities, and real-world performance evaluations.

• Collaboration is key, with the role intersecting with cross-functional teams across product, software, and safety domains.

• Engineers are expected to continuously monitor and fine-tune deployed models, ensuring high performance in volatile environments.

• The ideal candidate is someone who thrives under pressure, enjoys field challenges, and wants to create meaningful impact.

• This is not a purely academic or lab-based role but one that brings AI systems to life where it matters most — in the field.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Industrial Engineering, or related discipline is required.

• Hands-on experience with Python and SQL is essential for data manipulation and scripting purposes.

• Experience with containerization tools such as Docker is expected for environment management and deployment.

• Familiarity with machine learning frameworks like PyTorch or TensorFlow is important for model development and tuning.

• Exposure to production-level deployment of machine learning models, especially in real-world or edge environments, is critical.

• Understanding of computer vision or time-series analysis is an added advantage.

• Knowledge of Linux systems is mandatory, as development and deployment environments rely heavily on it.

• Experience with performance tuning, model monitoring, and real-time analytics is beneficial.

• Candidates must be open to frequent travel, up to 70%, including offshore deployments.

• Ability to work independently in non-routine environments with minimal supervision is important.

Additional Info:

• The role includes working closely with product teams and HSE professionals to ensure operational goals are aligned.

• Engineers will be required to provide training to field personnel, educating them on system usage and interpreting AI outputs.

• They will be expected to identify bottlenecks and data drift issues, continuously optimizing model behavior and output reliability.

• Candidates should be comfortable working in fast-paced startup environments with high ambiguity and evolving priorities.

• This position offers significant ownership over AI systems deployed at client sites, influencing how safety decisions are made.

• Communication and documentation skills are critical, especially when translating technical concepts to field personnel.

• Compensation will be competitive, with a focus on performance and impact.

• Candidates will work alongside a diverse and multidisciplinary team with deep domain knowledge in Oil & Gas operations.

• The company supports rapid professional growth, exposure to cutting-edge deployments, and opportunities to take on leadership.

• Successful candidates will leave a lasting impact on industrial safety and lives through AI-driven decision-making.

Please click here to apply.

✖

Before you go further ...

or

Direct apply link!